blackscholes_numba.py 文件源码

def black_scholes_numba(stockPrice, optionStrike,
                        optionYears, Riskfree, Volatility):
    callResult = np.empty_like(stockPrice)
    putResult = np.empty_like(stockPrice)

    S = stockPrice
    X = optionStrike
    T = optionYears
    R = Riskfree
    V = Volatility
    for i in range(len(S)):
        sqrtT = math.sqrt(T[i])
        d1 = (math.log(S[i] / X[i]) + (R + 0.5 * V * V) * T[i]) / (V * sqrtT)
        d2 = d1 - V * sqrtT
        cndd1 = cnd_numba(d1)
        cndd2 = cnd_numba(d2)

        expRT = math.exp((-1. * R) * T[i])
        callResult[i] = (S[i] * cndd1 - X[i] * expRT * cndd2)
        putResult[i] = (X[i] * expRT * (1.0 - cndd2) - S[i] * (1.0 - cndd1))

    return callResult, putResult